Skills : Python, PyTorch,
Works on pretraining and post-training of foundation models — architecture experiments, training efficiency, alignment techniques (RLHF, DPO), and scaling research, often in collaboration with research scientists.
Job Description:
Works on pretraining and post-training of foundation models — architecture experiments, training efficiency, alignment techniques (RLHF, DPO), and scaling research, often in collaboration with research scientists.
Key Skills:
- Deep learning theory and practice, transformer architectures
- Large-scale distributed training experience
- Research methodology, experiment design, reading/implementing papers quickly
- Python, PyTorch/JAX at an advanced level
- RLHF/DPO/alignment techniques knowledge
Experience Required:
- MS/PhD in ML/CS common, though strong independent research or open-source contributions can substitute
- 2–6 years in ML research or research engineering roles